2009/11/09 by A. L. Barbieri, Alan Barbieri, Barbieri, A. L. +11
Computer Science · Earth and Planetary Sciences · Engineering · Physics and Astronomy · #Computational Physics (physics.comp-ph) #Data Analysis #FOS: Physical sciences #Medical Image Segmentation Techniques #Remote Sensing and Land Use #Remote-Sensing Image Classification #Statistics and Probability (physics.data-an) #physics.comp-ph #physics.data-an
paper · pdf · doi:10.48550/arxiv.0911.1759
6 pages, 3 figures and 6 tables
arxiv created 2009/11/09 · openalex publication_date 2009/11/09 · arxiv updated 2009/12/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
An entropy-based image segmentation approach is introduced and applied to color images obtained from Google Earth. Segmentation refers to the process of partitioning a digital image in order to locate different objects and regions of interest. The application to satellite images paves the way to automated monitoring of ecological catastrophes, urban growth, agricultural activity, maritime pollution, climate changing and general surveillance. Regions representing aquatic, rural and urban areas are identified and the accuracy of the proposed segmentation methodology is evaluated. The comparison with gray level images revealed that the color information is fundamental to obtain an accurate segmentation.